Threshold factor models for high-dimensional time series
Threshold factor models for high-dimensional time series
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DOI：
10.1016/j.jeconom.2020.01.005
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发表时间：
2018-09
影响因子：
6.3
通讯作者：
Xialu Liu;Rong Chen
中科院分区：
文献类型：
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作者：
Xialu Liu;Rong Chen
我们考虑了一个阈值因子模型的高维时间序列，其中的动态时间序列被假定为切换不同的制度，根据阈值变量的值。这是一个扩展的阈值建模的因素结构下的高维时间序列设置。具体而言，在每个阈值制度，时间序列被假定为遵循一个因素模型。制度转换机制在因素加载矩阵中产生结构性变化。它提供了灵活性，在处理的情况下，基本状态可能会随着时间的推移而变化，经常观察到在经济时间序列和其他应用程序。我们开发的程序估计的加载空间，因子的数量和阈值，以及识别的阈值变量，它管理的政权变化机制。理论性质进行了研究。仿真和真实的数据的例子来说明所提出的方法的性能。
We consider a threshold factor model for high-dimensional time series in which the dynamics of the time series is assumed to switch between different regimes according to the value of a threshold variable. This is an extension of threshold modeling to a high-dimensional time series setting under a factor structure. Specifically, within each threshold regime, the time series is assumed to follow a factor model. The regime switching mechanism creates structural changes in the factor loading matrices. It provides flexibility in dealing with situations that the underlying states may be changing over time, as often observed in economic time series and other applications. We develop the procedures for the estimation of the loading spaces, the number of factors and the threshold value, as well as the identification of the threshold variable, which governs the regime change mechanism. The theoretical properties are investigated. Simulated and real data examples are presented to illustrate the performance of the proposed method.